---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- abdouaziiz/wolof_lam_asr
metrics:
- wer
model-index:
- name: whisper-m-wo
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: abdouaziiz/wolof_lam_asr
      type: abdouaziiz/wolof_lam_asr
    metrics:
    - name: Wer
      type: wer
      value: 0.2595195074616877
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# whisper-m-wo

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the abdouaziiz/wolof_lam_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4811
- Wer: 0.2595

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40
- training_steps: 16000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.7816        | 0.3912 | 1000  | 0.7274          | 0.6369 |
| 0.6368        | 0.7825 | 2000  | 0.6093          | 0.5042 |
| 0.3921        | 1.1737 | 3000  | 0.5506          | 0.4280 |
| 0.3494        | 1.5649 | 4000  | 0.5247          | 0.3115 |
| 0.3264        | 1.9562 | 5000  | 0.4907          | 0.3293 |
| 0.1734        | 2.3474 | 6000  | 0.4968          | 0.2973 |
| 0.1808        | 2.7387 | 7000  | 0.4811          | 0.2595 |
| 0.1064        | 3.1299 | 8000  | 0.4989          | 0.2490 |
| 0.0802        | 3.5211 | 9000  | 0.4975          | 0.2275 |
| 0.0745        | 3.9124 | 10000 | 0.4883          | 0.2429 |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1